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Location aware code offloading on mobile cloud with QoS constraint

机译:使用QoS约束将移动云上卸载的位置感知代码

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Mobile applications can be enhanced to a great extent by using the offloading mechanism in an energy efficient manner to the bounty resourceful clouds. Due to the huge demand of smart phones, the issue of providing more processing capability to this resource constraint device is getting more concern now-a-days. In this paper, a method level offloading mechanism has been proposed where no prior image of the mobile device is needed to be transferred to the cloud. The application is partitioned at different points where the migration of the execution thread is performed from mobile device to nearby resourceful cloud to get the best execution performance in optimal energy cost. The mobile can complete the execution after the partitioned thread returns back from the cloud to the device. This mechanism increases scalability as well as performance in the form of faster execution speed of the mobile devices. Moreover, we consider the mobility of the mobile device and propose a solution to find the best cloud instance on the move. To find out which cloud to offload, the communication latency, capacity, and current load at individual clouds are considered to find out the best cloud to offload to ensure better service for the mobile device. The proposed solution has been simulated and compared against CloneCloud in two different simulation scenarios where we show that our method performs superior to CloneCloud.
机译:可以在很大程度上使用卸载机制以节能的方式来提高移动应用,以节能的方式到赏金高兴的云。由于智能手机的巨大需求,为此资源约束设备提供更多处理能力的问题正在越来越受到令人满意的。在本文中,提出了一种方法级卸载机制,其中需要移动设备的现有图像来传送到云。该应用程序在不同点处划分,其中执行线程的迁移从移动设备执行到附近的云云以获得最佳能量成本的最佳执行性能。在分区线程从云返回到设备后,移动可以完成执行。该机制增加了可扩展性以及移动设备的更快执行速度的形式的性能。此外,我们考虑移动设备的移动性,并提出了一种解决方案,以便在移动上找到最佳云实例。要了解卸载的云,各个云的通信延迟,容量和当前负载被认为是找出最佳云以卸载,以确保更好地为移动设备服务。已经模拟了所提出的解决方案,并在两个不同的模拟场景中与CloneCloud进行了比较,我们表明我们的方法优于Clonecloud。

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